A Deep Learning Alternative Can Help AI Agents Gameplay the Real World A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

The future of zero-trust is about embedding resilience into every facet of an organisation. To achieve this, SRM leaders must reimagine their strategies to address emerging challenges and ...

After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, researchers organized them into a 'periodic table of machine learning' that can help scientists ...

Researchers at Northwestern Engineering have developed a scientific machine learning framework that predicts and inversely designs the mechanical behavior of spinodal metamaterials – specially ...

The chosen model was XGBoost, a gradient boosting ensemble learning method with high efficiency, flexibility, explainability, and an ability to handle missing values. 22 XGBoost has been used in many ...

The most common zero trust frameworks use static thresholds to grant levels of access to systems which could introduce false positives and incorrect access privileges to systems/networks. This ...

As artificial intelligence (AI) and machine learning (ML) continue to advance, Linux has established itself as the preferred environment for AI development. Its open source nature, security, stability ...

Short description The advancement of cybersecurity is propelled by adapting to new technologies and rising threats. From quantum cryptography to Zero Trust models and pioneering innovations from ...

This study explores the profound impact of emerging technologies on the Zero Trust paradigm and the challenges they present in the evolving cybersecurity landscape. As organizations grapple with ...